Pattern generating apparatus and pattern shape evaluating apparatus

ABSTRACT

Although there has been a method for evaluating pattern shapes of electronic devices by using, as a reference pattern, design data or a non-defective pattern, the conventional method has a problem that the pattern shape cannot be evaluated with high accuracy because of the difficulty in defining an exact shape suitable for the manufacturing conditions of the electronic devices. The present invention provides a shape evaluation method for circuit patterns of electronic devices, the method including a means for generating contour distribution data of at least two circuit patterns from contour data sets on the circuit patterns; a means for generating a reference pattern used for the pattern shape evaluation, from the contour distribution data; and a means for evaluating the pattern shape by comparing each evaluation target pattern with the reference pattern.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.13/294,828 filed Nov. 11, 2011, now U.S. Pat. No. 8,363,923 which is acontinuation of U.S. application Ser. No. 12/366,196 filed Feb. 5, 2009,now U.S. Pat. No. 8,077,962 which claims priority from Japanese PatentApplication No. 2008-031314 filed Feb. 13, 2008. The contents of eachare hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a pattern generating apparatus and apattern shape evaluating apparatus for evaluating the shapes of circuitpatterns for electronic devices by use of captured images of the circuitpatterns, the circuit patterns being manufactured on a wafer, a reticleor the like.

2. Background Art

In recent years, higher densification and integration of a semiconductordevice have been in progress for the purpose of improving theperformance of the semiconductor device and reducing the manufacturingcosts thereof. Producing semiconductor devices with much higher densityand integration requires development of lithography technologies forforming fine circuit patterns on a silicon wafer. The lithography is aprocess in which a mask is formed as a master pattern for circuitpatterns, and in which an exposure apparatus transfers the circuitpatterns of the mask onto a photosensitive light-receiving resin (calleda resist below) applied on a silicon wafer. The development of thelithography technologies is still in the trend toward finer patterning,thanks to various kinds of technological innovations in the phase shiftmask technology, the modified illumination technology, in the scanningexposure technique, in the field of chemically amplified resistmaterials, and in other related fields.

For a circuit pattern having a minimum size smaller than a wavelength oflight from an exposure light source, however, the conventionallithography technologies have a problem of an extreme reduction in atolerance (hereinafter, called a process window) allowed for eachprocess condition for lithography in the case where the processcondition varies from its optimum condition.

There are a wide range of factors of such extreme reduction of theprocess window, for example, which include: unevenness of illuminationaccompanying a wavelength shortening of light from an exposure lightsource; non-uniformity in processes such as antireflection, bake, anddevelopment; and variations in mask size. These factors of variations inthe lithography processes can be classified into an effective dose(simply called a dose below) that behaves in the same manner asvariations in an exposure light amount, and an effective focus (simplycalled a focus below) that behaves in the same manner as variations infocus.

For this reason, in the course of development of new semiconductordevices, semiconductor manufacturers make an attempt to increase processwindows through the following operations. In one of the operations, theprocess windows for a dose range and a focus range for manufacturingnon-defective patterns are figured out by measuring test patterns withuse of a length measuring SEM, the test patterns formed on a siliconwafer with the dose and focus being changed stepwisely (hereinafter,this operation is called a condition finding operation. See JapanesePatent Application Publication No. Hei 11-288879). In another one of theoperations, optimum conditions for lithography are derived by repeatedlyanalyzing the factors of dose variations and focus variations throughoptical simulations.

As for processes on patterns in size of 65 nm or finer, however, thecondition finding operation in the course of the development has adifficulty of finding the optimum process windows for all thecombinations of pattern shapes and pattern arrangements due to a highdensity of the patterns and high pattern complexity. Accordingly, moreimportance is now placed on the monitoring of a deformation of a patternshape caused by process variations in mass production processes.

An effective method for monitoring a deformation of a pattern shapecaused by process variations in mass production processes is a method ofobtaining a deformation amount in a pattern shape in a chip by comparingthe pattern shape in the chip with the pattern shape of a patternrepresenting a non-defective pattern whose pattern shape is not deformedat all by the process variations (hereinafter, the pattern is called areference pattern). As such pattern shape evaluation methods, there havebeen disclosed the inventions in which a pattern shape is evaluated byusing the design data on an electronic device as the reference pattern(Japanese Patent Application No. Hei 7-260699, Japanese PatentApplication Publications Nos. Hei 10-312461, 2002-6479 and 2001-338304(corresponding to U.S. Pat. No. 6,868,175)), and the invention in whicha pattern shape is evaluated by using a non-defective pattern as thereference pattern (Japanese Patent Application Publication No. Hei10-312461).

SUMMARY OF THE INVENTION

The inventions disclosed in Japanese Patent Application No. Hei7-260699, Japanese Patent Application Publications Nos. Hei 10-312461,2002-6479 and 2001-338304, however, have a problem that it is difficultto form a circuit pattern, having exactly the same shape as the circuitpattern of the design data, on a silicon wafer because of thelimitations of the performance of circuit pattern making apparatusessuch as a mask making apparatus and an exposure apparatus. Thus, theshape evaluation method using the circuit pattern of design data as areference particularly has a problem that the pattern shape isincorrectly evaluated due to a difference between the shapes of suchideal circuit pattern of the design data and actually formed circuitpattern. In order to address such a problem, Japanese Patent ApplicationPublication No. 2002-6479 discloses a method of evaluating a patternshape by using, as the reference pattern, a pattern that is obtained bydeforming a pattern shape of design data in advance to represent apattern shape to be actually formed on a silicon wafer. Nevertheless,due to the difficulty of completely predicting the pattern shape beforeits production, this method still has a problem that the disparitybetween the predicted pattern and an actually-produced pattern leads toan incorrect evaluation on the shape of the actually-produced pattern.

In consideration of the foregoing problems, one may come to theconclusion that an effective shape evaluation method is a method using,as a reference, the best pattern (a captured image of a perfect circuitpattern) among circuit patterns that are actually produced, as disclosedin Japanese Patent Application Publication No. Hei 10-312461. However,because each circuit pattern independently has locally-deformed portionslike edge roughness and the like caused during the manufacturing processof the electronic devices, even the technique in Japanese PatentApplication Publication No. Hei 10-312461 still suffers from the problemof the incorrect shape evaluation due to such locally-deformed portionsin the circuit patterns.

Furthermore, there are other problems. Although an SEM is usually usedas a means for capturing an image of a fine circuit pattern in order toevaluate the shape of the fine circuit pattern, the structure of the SEMinevitably causes the captured image to include noise and luminanceunevenness to a large extent. The noise and luminance unevenness exert aharmful effect on image processing of extracting a pattern shape from animage captured by the SEM. This harmful effect impedes extraction of theexact pattern shape of a non-defective pattern from a captured image.Consequently, pattern shapes cannot be evaluated correctly for a portionwhere the exact pattern shape of the non-defective pattern has failed tobe extracted. Moreover, it is not always guaranteed that a non-defectivepattern appropriate for the reference pattern, i.e., a non-defectivepattern free from the influence of process variations is formed on awafer.

Hence, in order to address these problems, the present invention hasbeen made as a pattern generating apparatus being used to evaluate ashape of a circuit pattern of an electronic device, and including: areference pattern generating means for generating, from contour datasets of at least two circuit patterns, a reference pattern used in apattern test, wherein the reference pattern generating means determinespoints that cross the at least two contour data sets and, in a directionapplied to each portion of the patterns, respectively correspond tocontour data of one circuit pattern and to contour data of anothercircuit pattern, and generates the reference pattern based on extractionof an average position between the corresponding point of the contourdata of the one circuit pattern and the corresponding point of thecontour data of the other circuit pattern, or a center position betweenthe corresponding point of the contour data of the one circuit patternand the corresponding point of the contour data of the other circuitpattern. In addition, the reference pattern generating means executescontour filling processing for a region interposed between the at leasttwo contour data sets, and generates the reference pattern based onthinning processing performed on the filled region.

In addition, the pattern generating apparatus according to the presentinvention pattern further includes a means for performing patternmatching between one and another one of the contour data sets todetermine a position for overlaying the contour data sets on oneanother, and the contour distribution data generating means generatesthe contour distribution data based on the position for overlaying thecontour data sets on one another.

The pattern generating apparatus according to the present inventionfurther includes a means for performing pattern matching between designdata and each of the contour data sets to determine a position foroverlaying the contour data set on the design data, and the contourdistribution data generating means generates the contour distributiondata based on the position for overlaying the contour data set on thedesign data.

Moreover, in the pattern generating apparatus according to the presentinvention, the contour distribution data generating means compares ashape of each of the contour data sets with a default value of the shapeof the circuit pattern, and generates the contour distribution data onlyby using the contour data sets satisfying the default value of the shapeof the circuit pattern.

Also, in the pattern generating apparatus according to the presentinvention, the reference pattern generating means figures out adistribution of contours from the contour distribution data, and setsthe reference pattern within a range of the distribution of contours.

Additionally, in the pattern generating apparatus according to thepresent invention, the reference pattern generating means generates thereference pattern from the contour distribution data in reference to theshape of the design data of the circuit pattern.

Alternatively, in order to address the aforementioned problems, thepresent invention has been made as a pattern shape evaluating apparatusincluding the contour distribution data generating means, the referencepattern generating means and a shape evaluation means for generating ashape evaluation value of an evaluation target pattern with respect tothe reference pattern by comparing the reference pattern with theevaluation target pattern.

Moreover, the pattern shape evaluating apparatus according to thepresent invention further includes a quality determination means fordetermining whether the evaluation target pattern is defective or not,by using the shape evaluation value.

In addition, in the pattern shape evaluating apparatus according to thepresent invention, the shape evaluation means calculates, as the shapeevaluation value of the evaluation target pattern, a gap between thereference pattern and the evaluation target pattern is measured, or anyof an average of the gaps, a dispersion of the gaps, and an area of theevaluation target pattern to the reference pattern, or determine, as theshape evaluation value, whether the evaluation target pattern existsoutside or inside a pattern shape deformation tolerance provided to thereference pattern. Then, the quality determination means determineswhether the evaluation target pattern is defective or not by comparingthe shape evaluation value with a default value for determining whetherthe evaluation target pattern is defective or not According to thepresent invention, a pattern shape evaluating apparatus includes: all ofor a part of the contour distribution data generating means, thereference pattern generating means, the shape evaluation means and thequality determination means; an imaging means for obtaining a capturedimage of the evaluation target pattern and captured images of the atleast two circuit patterns for generating the reference pattern; a meansfor extracting contour data of the circuit patterns from the capturedimages; and a data storage means for storing the captured images, thecontour data sets, the contour distribution data, and the referencepattern, the shape evaluation value and data on the qualitydetermination result, which are obtained used and obtained through thepattern shape evaluation.

The pattern shape evaluating apparatus according to the presentinvention further includes a means for generating, from the design dataof the circuit patterns, a recipe for obtaining a captured image of eachof the circuit patterns by the imaging means.

Moreover, the pattern shape evaluating apparatus according to thepresent invention further includes a data display means for displayingthe contour distribution data, the reference pattern and the data on theshape evaluation result.

Further, the pattern shape evaluating apparatus according to the presentinvention further includes a data input means for reflectinginstructions from a user into the reference pattern generating means,the shape evaluation means and the quality determination means. Then,the reference pattern generating means, the shape evaluation means andthe quality determination means generate the reference pattern andperform the shape evaluation on the basis of instruction data from thedata input means.

In order to address the foregoing problems, the pattern generatingapparatus according to the present invention further includes a datainput means for reflecting instructions from a user into the referencepattern generating means, and the reference pattern generating meansgenerates the reference pattern on the basis of instruction data fromthe data input means.

Furthermore, in order to address the foregoing problems, a pattern shapeevaluating apparatus according to the present invention generates animage of a wafer map indicating the shape evaluation value and a resultof the quality determination, and displays the image of the wafer map onthe data display means.

Hence, according to the present invention, a reference pattern used inshape evaluation of circuit patterns of electronic devices is generatedfrom captured images of multiple circuit patterns. Thus, the presentinvention enables the generation of the reference pattern which issuitable for the manufacturing conditions for circuit patterns and isless affected by distortion of each of the circuit patterns. Bycomparing each evaluation target pattern with this reference patter, thepattern shape evaluation can be performed with high accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart showing a pattern shape evaluation methoddescribed in Embodiment 1 of the present invention.

FIG. 2 is an overview diagram of the configuration of a pattern shapeevaluating apparatus according to the present invention.

FIG. 3 is a diagram showing patterns of different wafers, patterns ofdifferent shot areas, patterns of different chips, and patterns of thesame chip.

FIGS. 4A and 4B are diagrams of a captured image of a pattern and acontour data set of the pattern extracted from the captured image.

FIGS. 5A to 5H are diagrams showing a procedure of overlaying contourdata sets on one another.

FIG. 6 is a flowchart showing a procedure of generating contourcomposite data.

FIGS. 7A and 7B are diagrams showing a procedure of overlaying contourdata sets of the same focus of view (FOV).

FIG. 8 is a flowchart showing a procedure of generating contourcomposite data from contour data sets of the same FOV.

FIG. 9 is a diagram showing a method of generating a reference patternfrom contour composite data by using design data as a reference.

FIG. 10 is a flowchart showing one method of generating a referencepattern from contour composite data.

FIG. 11 is a flowchart showing another method of generating a referencepattern from contour composite data.

FIGS. 12A to 12F are diagrams showing a method of determining points ofthe reference pattern from contour distribution data.

FIG. 13 is a flowchart showing a processing procedure of generating ashape evaluation value of an evaluation target pattern by comparing theshapes of the reference pattern and the evaluation target pattern.

FIGS. 14A to 14D are diagrams showing an example of shape comparisonbetween the reference pattern and the evaluation target pattern.

FIGS. 15A and 15B are diagrams showing table data in which results ofthe shape evaluation values are stored.

FIG. 16 is a flowchart showing a procedure of determining whether apattern is defective or not.

FIGS. 17A to 17C are diagrams showing an example of measurement of apattern gap.

FIG. 18 is a view showing image data providing a result of qualitydetermination to users.

FIG. 19 is a flowchart showing a procedure of overlaying contour datasets on one another with high accuracy.

FIGS. 20A and 20B are views showing a rotation and shift of a contourdata set and its correction result.

FIGS. 21A and 21B are views showing an example of combining contour datasets.

FIG. 22 is a flowchart showing an image capture sequence of an SEM.

FIG. 23 is a diagram of a layout for the image capture sequence of theSEM.

FIGS. 24A to 24D are diagrams showing an example of determining areference pattern from contour distribution data.

FIGS. 25A to 25C are diagrams showing design data of a circuit patternand a relationship between the design data and the center line of thepattern.

FIGS. 26A and 26B are diagrams showing an example of generating areference pattern from contour distribution data.

FIG. 27 is a flowchart showing a procedure of generating contourcomposite data with a largely-deformed pattern excluded from patterns tobe used for a contour composite.

DESCRIPTION OF SYMBOLS

-   201 wafer-   202 electro optical system-   203 electron gun-   204 electron beam-   205 condenser lens-   206 deflector-   207 ExB deflector-   208 object lens-   209 secondary electron detector-   210, 211 reflection electron detector-   212 to 214 analog to digital convertor-   215 processing controller-   216 display-   217 stage-   219 stage controller-   220 deflection controller-   221 focus controller-   223 storage device-   225 imaging recipe generator-   230 design system-   251 central processing unit-   252 image memory-   253 large-scale integration-   301, 305 wafer-   302 shot area-   303 chip-   304 pattern in chip-   306 relationship between patterns of different wafers-   307 relationship between patterns of different shot areas-   308 relationship between patterns of different chips-   309 in-FOV pattern-   401 white band-   402 background-   403 contour of pattern-   501 shift amount A-   502 shift amount B-   503 shift amount C-   504 contour overlay position-   701 shift amount-   702 to 704 contour composite point-   705 to 707 composite region-   708 coordinates-   900, 1211 design data-   901 center line of design data-   902 normal line to center line of design data-   903, 2603 outer border of contour distribution-   904 center of contour distribution-   905, 2601 inner border of contour distribution-   906, 907, 908 intersection of center of contour distribution and    normal line-   909, 910 end point of center line of design data-   1201 inner border-   1202 outer border-   1203 center position of contour distribution-   1210 cursor-   1212 center line-   1213, 1214 point of reference pattern-   1401, 1702, 2103 reference pattern-   1402 evaluation target pattern-   1403 gap-   1404 band-   1405 defective portion of evaluation target pattern-   1406 tolerance of shape deformation with respect to reference    pattern-   1407, 1408 region-   1409 point on reference pattern-   1410 point-   1701 contour data region-   1703, 1704, 1705 pattern-   1801 quality determination result-   2001, 2002 contour data-   2101 contour data A-   2102 contour data B-   2003 position correction amount-   2301 design layout-   2302 focus point-   2303 addressing point-   2304 brightness/contrast point-   2305 shape evaluation point-   2306 automatic astigmatism point-   2401, 2402 point-   2403, 2404 contour distribution border-   2501 vertex coordinate data-   2502 center line of design data-   2602 center pattern

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereinafter, preferred embodiments will be described with reference tothe drawings.

First Embodiment

FIG. 2 shows an overview of configuration blocks of a scanning electronmicroscope a scanning electron microscope (abbreviated as SEM, below)that captures images of circuit patterns according to the presentinvention. An electro-optical system 202 includes: an electron gun 203that generates an electron beam (primary electrons) 204; a condenserlens 205 that converges the electron beam 204 generated from theelectron gun 203; a deflector 206 that defects the converged electronbeam 204; an ExB deflector 207 that detects secondary electrons; and anobject lens 208 that causes the converged electron beam 204 to form animage on a semiconductor wafer 201. The wafer 201 is placed on an XYstage 217. After that, the deflector 206 and the object lens 208 controlthe radiating position and the diaphragm of the electron beam so thatthe electron beam can be radiated and focused on a desired position onthe wafer 201 placed on the XY stage 217. Meanwhile, the XY stage 217also allows a desired position of the wafer 201 to be imaged by movingthe wafer 201. Here, changing an observation position by the XY stage217 is referred to as a stage shift, whereas changing an observationposition through defection of the electron beam by the deflector 206 isreferred to as a beam shift. From the wafer 201 irradiated with theelectron beams, secondary electrons and reflection electrons areemitted. The secondary electrons are detected by a secondary electrondetector 209, while the reflection electrons are detected by reflectionelectron detectors 210, 211. The reflection electron detectors 210, 211are arranged at different locations. The secondary electrons andreflection electrons detected by the secondary electron detector 209 andthe reflection electron detectors 210, 211 are converted into digitalsignals by analog to digital (A/D) converters 212, 214, 213,respectively. Then, the digital signals are inputted to a processingcontroller 215, and are stored in an image memory 252. A centralprocessing unit (CPU) 251, an large-scale integration (LSI) 253 that isimage processing hardware, and the like perform image processing on thestored digital signals according to a purpose and thereby evaluate theshapes of circuit patterns. More specifically, the processing controller215 transmits control signals to a stage controller 219 and a deflectioncontroller 220 in order to capture images of shape evaluation pointsbased on an imaging recipe being generated by an imaging recipegenerator 225, which will be described later, and indicating a procedureof shape evaluating. Then, the processing controller 215 performsprocessing and control for various types of image processing and thelike on the observed images on the wafer 201 to evaluate the shape ofthe circuit pattern.

Here, the processing controller 215 is connected to: the stagecontroller 219 that controls the position and movement of the stage 217,including global alignment control for correcting a shift of the wafer201 from the origin or correcting rotation of the wafer 201 by observingglobal alignment marks on the wafer 201 with an optical microscope (notshown) or the like; the deflection controller 220 that controls thedeflector 206 to control the beam shift (beam deflection) of theelectron beam; and a focus controller 221 that controls the object lens208 to perform focus control. In addition, the processing controller 215has functions such as a graphical user interface (GUI) that is connectedto a display 216 including an input means and shows a user images, shapeevaluation results and the like on the display 216. Incidentally,although this embodiment shows the two detectors provided for reflectionelectron images, the number of detectors for reflection electron imagescan be increased or decreased. In addition, the aforementionedprocessing and control can be performed with the control, which is to beperformed by the processing controller 215, partially or entirelyallocated to another computer or the like including a central processingunit (CPU) and a memory capable of cumulatively storing images.

The processing controller 215 is further connected to the imaging recipegenerator 225 through a network, bus or the like. The imaging recipegenerator 225 generates the imaging recipe including the coordinates ofa circuit pattern; a template of the design data for positioningcorresponding to the coordinates; information on imaging conditions(including an imaging scale factor, image quality and the like) for SEMobservation; and the like. In order to obtain design data, the imagingrecipe generator 225 is connected to a design system 230 such as anelectronic design automation (EDA) tool through a network or the like.The imaging recipe generator 225 generates an imaging recipe, by usingdesign data and information on the image pickup points on a wafertargeted for the shape evaluation, and is equivalent to an imagingrecipe generator disclosed, for example, in Japanese Patent ApplicationPublication No. 2006-3517146. The concept of generating an imagingrecipe from design data was proposed a long time ago, and thisdescription is not intended to limit imaging recipe generation methodsand apparatuses to which the present invention is applicable. Ingeneral, the imaging recipe generation is executed through softwareprocessing with a computer in which a central processing unit (CPU),memory and the like are mounted, or through hardware processing withhardware in which a central processing unit (CPU), application specificintegrated circuits (ASIC), field programmable gate array (FPGA), memoryand the like are mounted.

Next, an imaging sequence for observing a desired shape evaluation point(abbreviated as EP below) on a wafer will be described by use of FIG.22. FIG. 23 shows setting examples of an addressing point (abbreviatedas AP below) 2303, an auto-focus point (abbreviated as FP below) 2302,an automatic astigmatism point (abbreviated as SP below) 2306 that is anastigmatism correction point, a brightness/contrast point (abbreviatedas BP below) 2304 that is a brightness/contrast adjustment point, withrespect to an EP 2305 on a design layout 2301. Based on the informationon the design data and the shape evaluation point, the imaging recipegenerator 225 generates, as the imaging recipe, an image capture pointand image capture conditions (including an imaging scale factor, imagequality and the like) in the imaging sequence, and also shape evaluationconditions for the EP. The imaging recipe thus generated is stored andmanaged, for example, in a storage device 223.

In the first place, the wafer 201 as a sample is placed on the stage 217(2201). Then, the processing controller 215 calculates the shift fromthe origin and the rotational shift of the sample on the basis of aresult from an observation of global alignment marks on the sample bymeans of the optical microscope (not shown) or the like, and correctsthese shifts by controlling the stage 217 through the stage controller219 based on the calculated shift amounts (2202). After that, theprocessing controller 215 moves the stage 217 to shift the image captureposition to the AP according to the coordinates of the image capturepoint and the imaging conditions generated by the imaging recipegenerator 225, and then captures an image of the AP under the imagingconditions with a smaller scale factor than when the image of the EP iscaptured (2203). Here, more detailed explanation is provided for the AP.In a trial to directly observe the EP, this observation target point maybe located out of the field of view of the SEM due to poor positioningaccuracy of the stage 217 and the like. To solve this problem, the AP isused as follows. Having the known coordinates, the AP generated by theimaging recipe generator 225 and registered in the storage device 223 inadvance is once observed for positioning. Then, the processingcontroller 215 performs matching of the design data template at the APgenerated by the imaging recipe generator 225 and registered in thestorage device 223 in advance, and the SEM image of the observed AP.Thereby, the processing controller 215 detects a shift vector betweenthe center coordinates of the design data template and the centercoordinates of the AP actually observed. Thereafter, the processingcontroller 215 moves the image capture position by controlling thedeflector 206 through the deflection controller 220 so that the beamshift (the radiation position of the beam is changed by tilting the beamradiation direction) can be performed by a distance obtained bysubtracting the shift vector from the relative vector between thecoordinates of the design data template and the coordinates of the EP.When the EP is observed after this positioning adjustment, the image ofthe EP can be captured with high coordinates accuracy (In general, thepositioning accuracy of the beam shift is higher than the positioningaccuracy of the stage). Thereafter, the processing controller 215performs control and processing to shift the image capture position tothe FP by the beam shift, to capture an image of the FP, to obtainparameters for autofocus and to perform the autofocus based on theobtained parameters (2204).

Subsequently, the processing controller 215 performs control andprocessing to shift the image capture position to the SP by the beamshift, to capture an image of the SP, to obtain parameters forastigmatism correction and to perform the automatic astigmatismcorrection based on the obtained parameters (2205).

Next, the processing controller 215 performs control and processing toshift the image capture position to the BP by the beam shift, to capturean image of the BP, to obtain parameters for brightness&contrastadjustment and to perform the brightness&contrast adjustment based onthe obtained parameters (2206). Incidentally, the addressing, theautofocus, the automatic astigmatism correction, the automaticbrightness&contrast adjustment in the aforementioned steps 2203, 2204,2205 and 2206 are performed in different manners depending on occasions.For example, one, some or all of the steps 2203, 2204, 2205 and 2206 areskipped; the order of executing the steps 2203, 2204, 2205 and 2206 ischanged as needed; or some of the AP, FP, SP and BP have the samecoordinates (for instance, the autofocus and the automatic astigmatismcorrection are preformed on the same point). In the last place, theprocessing controller 215 performs control and processing to shift theimage capture position to the EP by the beam shift, to capture an imageof the EP, to perform matching of the design data template at the EPregistered in the storage device 223 and the SEM image of the observedEP, and to calculate a shift amount of a shape evaluation target pointin the SEM image (2207).

After the imaging, the pattern shape evaluation according to the presentinvention is performed by use of the SEM image of the EP and the shiftamount obtained by the EP matching. In the pattern shape evaluation, areference pattern is firstly generated from captured images of multiplepatterns of different production points on a wafer or different wafersso that pattern deformation due to process variations, and pattern shapedistortion due to noise included in the images, and distortion due toroughness or the like included in each of the patterns can be eliminatedas much as possible. After that, the shapes of the reference pattern andthe evaluation target pattern are compared with each other, and therebya shape evaluation value of the evaluation target pattern is obtainedwith respect to the shape of the reference pattern. Note that, theaforementioned multiple patterns are those based on an equal shape inthe design data.

The multiple patterns are patterns, for example, under the followingconditions (A) to (D). FIG. 3 shows relationships under the conditions(A) to (D), and shows relationships among two wafers 301 and 305, a shotarea 302 in the wafer 301, a chip 303 in the shot area, and a pattern304 in the chip. Here, the shot area is an exposure area transferable atone time and multiple chips are included within one shot area.

(A) Multiple patterns from different wafers (an example 306)

(B) Multiple patterns from different shot areas (an example 307)

(C) Multiple patterns from different chips in the same shot area (anexample 308)

(D) Multiple patterns having different coordinates in the same chip (anexample 309)

The above conditions are only one example, and the reference pattern maybe generated by use of multiple patterns under a combination of theconditions (A) to (D).

Hereinafter, a pattern shape evaluation method according to the presentinvention will be described in detail.

FIG. 1 shows a flowchart of the pattern shape evaluation methodaccording to the present invention. The pattern shape evaluation methodis executed through software processing with use of the centralprocessing unit (CPU) 251, the image memory 252 and the like in theprocessor controller 215. Instead, the pattern shape evaluation methodmay also be executed through software processing with a centralprocessing unit (CPU), a memory and the like in a computer to whichimages and the design data template can be inputted from the electrooptical system 202 and the imaging recipe generator 225, respectively,via a LAN or a bus, or via a storage medium such as a portable memoryand a hard disk. Each of steps will be described below in detail.

Firstly, captured images of circuit patterns are read (101). The imagesused in the pattern shape evaluation are obtained by controlling theelectro optical system 202 according to the recipe, generated by theimaging recipe generator 225, for capturing the images of the evaluationtarget pattern and the multiple patterns that are under conditions suchas the above conditions A to D and are used for reference patterngeneration.

Next, contour lines of each of the circuit patterns are extracted fromthe image (102). Various methods for extracting contour lines have beenproposed. An applicable method here is, for example, the methoddisclosed in Japanese Patent Application Publication No. 2006-66478, themethod disclosed in “R. Matsuoka, New method of contour based mask shapecompiler, SPIE Proc 6730-21, 2007.9.21,” or the like. When the image ofthe pattern is captured by the SEM, inclined parts and protruding partsin the pattern are imaged as white-band-shaped images (hereinafter,referred to as white band images 401) on a background 402, as shown inFIG. 4A. With the application of any of the aforementioned methods andthe like, the white band images 401 can be extracted as a contour dataset 403 on a line image as shown in FIG. 4B. The image reading (101) andcontour extraction (102) are performed for all the images including theimages for the reference pattern generation and the image of theevaluation target pattern (103).

Then, the reference pattern is generated by use of multiple contour datasets extracted from the images for the reference pattern generation. Inorder to eliminate pattern shape deformation due to process variations,pattern distortion due to the roughness or the like occurred in each ofthe patterns, and contour distortion due to noise included in the imagesas much as possible, it is preferable to use a largest possible numberof patterns to generate the reference pattern.

Contour Compositing

As preparation for the reference pattern generation, multiple contourdata sets 2101 and 2102 extracted from the images are overlaid on oneanother, as shown in FIG. 21A, and thereby a composite of the contoursis generated (104). As described above, if the contour positions of thepatterns in the images are different among the contour data sets becauseof the problem of the positioning accuracy of the stage, the contourdata sets are overlaid on one another in consideration of the contourpositions in the images. An overlay position can be automaticallyidentified by use of the EP matching result that is used to identify theshape evaluation point. A method of automatically identifying theoverlay position is explained here by using FIGS. 5A to 5H. FIGS. 5A to5C show three images of contour data sets for the reference patterngeneration. Due to the problem of the stage positioning accuracy and thelike, the contour positions in the three images are different among thecontour data sets. FIG. 5D shows a design data template used formatching. As a result of the EP matching, shift amounts 501, 502 and 503of the images in FIGS. 5E, 5F and 5G from the design data template canbe detected. Based on these shift amounts, an overlay position 504 forthese three contour data sets is identified as shown in FIG. 5H. Therehave been various methods for detecting the shift amount from the designdata and the contour data by finding a matching position with highaccuracy, even though the two types of data have different shapes, whileabsorbing such a shape difference. The shift amount can be detected withapplication of the method disclosed, for example, in Japanese PatentApplication Publication No. 2007-79982.

FIG. 6 shows a processing flow of the contour data overlay. Firstly,multiple contour data sets (or images before contour extraction) areread (601). Then, matching of each of the contour data sets (or theimages before contour extraction) with the design data template isperformed (602). Based on the matching result, the shift amount of eachof the contour data sets from the design data template is calculated(603). After that, the multiple contour data sets are overlaid by usingthe shift amounts as references to generate a composite image (604). Thecontour composite image is written to a memory or the like (605).

In addition, even in the case where a single image includes multiplepatterns to be overlaid, the patterns can be overlaid easily by use ofthe shift amount obtained by the EP matching and pattern intervalsobtained from the design data. An example of overlaying multiplecontours of a contour data set of one image is described by use ofprocessing overview diagrams in FIGS. 7A and 7B, and a flowchart in FIG.8. Firstly, a contour data set is read (801). Then, pattern matching ofthe contour data set (or the image before contour extraction) with thedesign data template is performed (802, equivalent to the EP matching).Based on the pattern matching result, a shift amount (701 in FIG. 7A) iscalculated (803). After that, contour composite points 702 to 704 andcomposite regions 705 to 707 on the contour data set are determinedaccording to the shift amount 701 and the pattern arrangement intervalson the design data (804). Next, a contour composite image is generatedbased on the contour composite points 702 to 704 and the compositeregions 705 to 707 (805). FIG. 7B shows an image in which the contourdata of the composite regions 705 to 707 are overlaid on one anotherwith the contour composite points 702 to 704 arranged at coordinates 708in a contour composite image. In the last place, the contour compositeimage is written to the memory (806). Incidentally, a user can specifythe contour composite points and the composite regions through the inputmeans connected to the display 216. In this case, the contour data setis displayed on the display 216, and the contour composite points andthe composite regions specified through the input means are stored inthe memory. The contour data are combined based on the contour compositepoints and the composite regions, and the resultant image is written inthe memory.

FIG. 12A shows an example of a contour composite image. When theevaluation target patterns have different shapes attributed to processvariations and roughness or the like in individual patterns, a contourcomposite image obtained by overlaying the contours has a distributionof the pattern shapes (called a contour distribution below) as shown inFIG. 12B. A reference pattern 2103 as shown in FIG. 21B is generatedfrom such contour composite image (105).

Reference Pattern Generation

The reference pattern is determined from the distributed contours of thecontour composite image in accordance with a predetermined rule. Thepredetermine rule should be changed according to a purpose of shapeevaluation, and is not limited to those described herein. The followingdescription provides two examples of generating the reference patternfrom the contour composite image.

1) Average Shape in Contour Distribution

The reference pattern is formed by use of average points in the contourdistribution. The shape evaluation of the evaluation target pattern withrespect to the average pattern shape can be made by comparing the shapesof this reference pattern and the evaluation target pattern. FIG. 24Ashows a contour distribution, and shows an example of forming thereference pattern (shown by a broken line) by use of the average pointsin the contour distribution. FIG. 24C shows a graph of the number ofcontours on a straight line Q-P in the contour distribution, and shows apoint 2401 of the average reference pattern in the contour distributionon the Q-P line.

In order to determine the average point in the contour distribution, thenumber of overlapping contours needs to be stored as a pixel value ofthe contour composite image at the time of the generation of the contourcomposite image. Then, this contour composite image is processed throughthe moving average filter described in a chapter of “Smoothing and NoiseElimination” of p. 11 in “Tamura Hideyuki, Konputa gazo shori (computerimage processing), (hereinafter, called Reference Document 1)” or thelike, whereby the contour composite image having a peak at the averagepoint in the contour distribution is generated. Eventually, the peakpoints continuing in the contour distribution are identified, and thethus identified peak points are determined as the reference pattern (thebroken line in FIG. 24A).

2) Central Shape between Contour Distribution Borders

The reference pattern is formed by use of the center between contourdistribution range borders. The shape evaluation of the evaluationtarget pattern with respect to the center in the shape variation rangeof the evaluation target pattern can be made by comparing the shapes ofthis reference pattern and the evaluation target pattern. FIG. 24B showsthe same contour distribution as in FIG. 24A, and shows an example offorming the reference pattern (shown by a solid line) by use of thecenter in the contour distribution range. FIG. 24D shows a graph of thenumber of contours on a line Q-P, and shows contour distribution borders2403 and 2404 on the line Q-P and a point 2402 of the reference patternlocated on the center between the contour distribution borders 2403 and2404.

FIG. 10 shows a flowchart of a method of detecting the center betweencontour distribution borders from a contour composite image.

In the first place, a contour composite image is read (1001). Then,contour filling is performed (1002). FIG. 12B is an enlarged diagram ofa contour distribution in the contour composite image shown in FIG. 12A.The contour distribution includes a point where a contour exists, and apoint where no contours exist. The contour filling is processing inwhich the same value as a value of the contour is written to pixelswithin a range between the contours. For example, when the contourcomposite image is of binary data with a pixel value “1” at each pointwhere the contour exists and with a pixel value “0” at each point whereno contours exist, all the pixel values within the region between thecontours are changed to “1” as shown in FIG. 12C by applying an imageprocessing method such as a morphology filter (expansionprocessing→contraction processing) shown in a chapter “Contraction andExpansion” on p. 154 of Reference Document 1.

Then, by use of the data resulting from the contour filling, a centerposition 1203 in the contour distribution is detected (1003). Thiscenter position detection can be implemented with application ofthinning processing described in a chapter “Thinning” on p. 158 ofReference Document 1, for example. The thinning processing is processingfor figuring out the center line of a widely distributed pattern. Thecenter position 1203 in the contour distribution as shown in FIG. 12Dcan be obtained by thinning the filled contour distribution. This centerposition in the contour distribution is written as the reference patternto a memory or the like (1004).

Instead of use of the center position between the contour distributionborders, the position of the reference pattern may be determined by useof points 1213 or 1214, which are located several pixels shifted fromthe center position 1203 in the contour distribution toward an outerborder 1202 or an inner border 1201, respectively, as shown in FIG. 12F.FIG. 11 shows a processing flow of a method of generating such referencepattern. Here, since steps 1101 to 1103 include processing equal to theprocessing in steps 1001 to 1003 in the processing flow in FIG. 10, theexplanation thereof is omitted.

After the center position in the contour distribution is identified, theinner border 1201 and the outer border 1202 shown in 12D are identified(1104). Assume that a contour distribution image in which the pixelvalues of the filled contour are “1” while the pixel values of theregion other than the contour are “0.” In this case, a point where thepixel values are changed from “0” to “1” when viewed from a center line1212 of an entire circuit pattern shape is determined as the innerborder 1201, while a point where the pixel values are changed from “1”to “0” when viewed from the center line 1212 is determined as the outerborder 1202. The center line of the pattern shape in the contourdistribution image can be determined by use of the shift amount of thecontour data set (one of the multiple patterns) from the design data1211 obtained by the EP matching; and the center line 1212 of the entirecircuit pattern of the design data. A method of finding the center lineposition of the pattern shape from the design data will be describedwith reference to FIGS. 25A to 25C.

The design data is provided by a design system 230 or the like as a setof vertex coordinate data 2501 of multiple vertexes that constitute aclosed figure of the pattern as shown in FIG. 25A. The pattern of thedesign data is obtained by connecting these vertex coordinates with astraight line. The pattern composed of the straight lines is drawn andan image having the inside of the pattern filled as shown in FIG. 25B iscreated. In this image, for example, the straight lines and the filledregion of the design data are set to have the pixel values “1,” and theregion other than these are set to have the pixel values “0.”

Subsequently, a center line 2502 in the pattern shape of the design dataas shown in FIG. 25C is figured out by performing the aforementionedthinning processing on the image having the inside of the pattern thusfilled.

The center line 1212 in the contour distribution image can be figuredout based on the center line position of the pattern shape of the designdata and the shift amount obtained by the EP matching. Then, the innerborder 1201 and the outer border 1202 can be figured out according tothe positional relationships between the center line 1212 and the pointswhere the pixel values are changed.

After the inner border 1201 and the outer border 1202 are found by useof the center position of the entire pattern shape, the position of thereference pattern is determined based on the center position 1203 in thecontour distribution (1105). By use of FIG. 26, description will beprovided for an example in which the reference pattern is determinedaccording to a rule of using “a point of the L-th pixel from the centerposition in the contour distribution toward the outer border.”

The aforementioned morphology filter (expansion processing) is firstlyapplied to the pattern of the center position 1203 in the contourdistribution. The expansion processing is processing of expanding thepattern width. The pattern of the center position in the contourdistribution has a width of one pixel. When this pattern is onceprocessed through the expansion processing, a pattern thus generated hasa width of 3 pixels whose center pixel is the pixel of the centerposition in the contour distribution. FIG. 26 shows an example of thisexpansion processing. FIG. 26 shows a center pattern 2602 and an innerborder 2601 and an outer border 2603 of a contour distribution. When thecenter pattern 2602 is once processed through the expansion processing,the center pattern 2602 is expanded by one pixel of its either side asshown in an enlarged window in FIG. 26A. The pixels newly added by theexpansion processing each exist at a point of a first pixel from thecenter pattern 2602. Thus, a distance value “1” indicating a distancefrom the center pattern is written to each of the pixels newly added bythe first expansion processing. By iteratively performing the expansionprocessing and writing the distance value, the distance values can bewritten to pixels existing between the inner border 2601 and the outerborder 2603 of the contour distribution, as shown in an enlarged windowFIG. 26B. The point of the L-th pixel from the center toward the outerborder in the contour distribution can be easily found by use of therelationship between the thus obtained distance information on thedistance from the center, and the inner border 2601 and the outer border2603 of the contour distribution.

In addition, the reference pattern can be formed by use of the centerposition between contour distribution borders on the basis of thepattern shape of the design data. FIG. 9 is a diagram in which designdata 900 is overlaid on an inner border 905 and an outer border 903 of acontour distribution according to the shift amount obtained by the EPmatching. Center positions 908 between the contour distribution borderseach exist on a straight line (normal line) 902 drawn in a direction ofthe normal to a center line 901 of the design data 900 (but in adirection extending in a fan-like fashion at both end points 909 and 910of the center line). More specifically, the center position 908 betweenthe contour distribution borders can be found as the midpoint between anintersection point 906 of the inner border 905 and the straight line(normal line) and an intersection point 907 of the outer border 903 andthe straight line (normal line). In the last place, a reference pattern(that is, 904) is formed by finding approximate straight lines andapproximate curved lines from the midpoint distribution.

In addition, as shown in FIG. 12E, a user may also be allowed todetermine the position of the reference pattern by operating a cursor1210 through the input means connected to the display 216. In this case,the contour distribution image is displayed on the display 216, and thusthe user is allowed to determine the reference pattern while checkingthe contour distribution image. Note that, the reference pattern thusdetermined is written to the memory or the like (1106).

Shape Comparison Test

Next, the shape of the reference pattern generated from the contourcomposite image and the shape of the evaluation target pattern arecompared with each other and the shape evaluation value of theevaluation target pattern with respect to the shape of the referencepattern is generated (106). The shape evaluation value is data used todetermine whether the below mentioned evaluation target pattern isdefective or not.

FIG. 13 shows a processing flow. Firstly, the reference pattern is read(1301). Then, the contour data set of the evaluation target pattern isread (1302). After that, the shape evaluation value of the evaluationtarget pattern with respect to the shape of the reference pattern isobtained by use of the reference pattern in any of methods illustratedbelow (1303), and the obtained shape evaluation value is written to thememory or the like (1304). These operations are iteratively executed forall the contours (1305). Three methods for generating the shapeevaluation value will be described below with use of FIGS. 14A to 14D.However, these methods are not intended to limit the method ofgenerating the shape evaluation value, because any method that allowsquality determination of the evaluation pattern is usable

(1) Pattern Gap

FIG. 14A shows an image in which a reference pattern 1401 and anevaluation target pattern 1402 are overlaid on each other according tothe shift amount obtained by the EP matching.

FIG. 14B shows an example in which a gap between the reference pattern1401 and the evaluation target pattern 1402 having a relationship shownin FIG. 14A is measured and the gap value thus obtained is determined asthe shape evaluation value of the evaluation target pattern. The gapmeasurement can be performed by measuring a gap 1403 between, forexample, a point 1409 on the reference pattern, and a point 1410 of theevaluation target pattern existing in a direction normal to thereference pattern at the point 1409. If the gap measurement isperformed, for example, on every second pixel on the reference pattern,how much the shape of the evaluation target pattern is deformed from thereference pattern is quantified. Instead, an average or dispersion ofpattern gaps may be calculated and used as the shape evaluation value.For example, FIG. 17A shows an example in which a gap L(n) (n: thenumber of pixels constituting a pattern 1703) between a referencepattern 1702 and the pattern 1703 is measured. In the gap measurement,the gap value is obtained in units of pixels or sub-pixels constitutingthe pattern 1703. As a result, a large number of gap values L(n) areobtained for a contour data region 1701. For this reason, the shapeevaluation value is simplified by calculating the gap average (ΣL(n)/n))or the gap dispersion (Σ(L(n)−ΣL(n)/n))̂2/n) from the obtained gap valuesL(n). A pattern 1704 as shown in FIG. 17B has a shapeexpanded/contracted, as a whole, from the shape of the reference pattern1702, for example. In this case, the shape evaluation values tend tohave a small gap dispersion value and a large gap average value.Instead, a pattern 1705 as shown in FIG. 17C has a shape having a localdistortion from the shape of the reference pattern 1702. In this case,the shape evaluation values tend to have a large gap dispersion value.The shape evaluation value thus obtained is written, as tableinformation as shown in FIG. 15A, to the memory or the like.

(2) Shape Deformation Tolerance

FIG. 14C shows an example in which a band 1404 indicating a tolerance ofshape deformation is set in the reference pattern 1401 having therelationship shown in FIG. 14A, and in which a determination result asto whether the evaluation target pattern 1402 is located inside oroutside the band is used as the shape evaluation value. For instance,the expansion processing with the aforementioned morphology filter isapplied to the reference pattern, and thereby the reference pattern isexpanded to cover a tolerable region 1406 of the shape deformation. Inthis way, the band 1404 indicating the shape deformation tolerance fromthe reference pattern 1401 can be generated. This band 1404 and theevaluation target pattern 1402 are overlaid on each other according tothe shift amount obtained by the EP matching, and a determination ismade as to whether each point on the evaluation target pattern 1402exists inside or outside the band 1404. Here, a portion of theevaluation target pattern 1402 existing outside the band 1404 isreferred to as a defective portion 1405. This result is written as theshape evaluation value, i.e., as table information shown in FIG. 15B tothe memory or the like.

(3) Pattern Area

FIG. 14D shows a region 1407 surrounded by the reference pattern 1401and a region 1408 surrounded by the evaluation target pattern 1402. Theareas of these regions are figured out by counting the number of pixelssurrounded by each of the patterns. An area ratio of the evaluationtarget pattern 1402 to the reference pattern 1401 is written as theshape evaluation value to the memory or the like.

Quality Determination

Whether a pattern is defective or not is determined by use of the shapeevaluation value obtained as described above (107). FIG. 16 shows aprocessing flow of this quality determination. In the first place, theshape evaluation value of each of the evaluation target patterns is read(1601). Then, the shape evaluation value is compared with data (adefault value) defining information on a non-defective pattern shape,and whether the evaluation target pattern is defective or not isdetermined (1602). This determination is performed for all theevaluation target patterns (1605), and the evaluation results are lastlywritten to the memory or the like (108/1606). In addition, in order forthe user to easily and distinctively recognize points on a wafer wherethere are patterns determined as non-defective and patterns determinedas defective, a wafer map image is generated as shown in FIG. 18 anddisplayed on the display. The wafer map image thus generated shows thepositions of the patterns on a wafer 1802 and an area 1801 in whichnon-defective patterns exist. From this wafer map, the user canrecognize a point on the wafer where pattern shapes are largely deformeddue to process variations.

The method of determining whether or not the shape evaluation value istolerable depends on the type of the generated shape evaluation value.The following shows the determination methods for the aforementionedshape comparison values (1) to (3).

(1) Pattern Gap

The gap value between an evaluation target pattern and the referencepattern obtained through the shape evaluation is compared with the gapvalue between a non-defective pattern and the reference pattern obtainedin the same manner, a portion of the evaluation target pattern having agap larger than the corresponding gap of the non-defective pattern isdetermined as a defective portion, and an evaluation target patternincluding a portion determined as defective is determined as defective.In addition, even when the average or dispersion of the pattern gaps isused as the shape evaluation value, the pattern defect is determinedthrough threshold processing in a similar manner.

(2) Shape Deformation Tolerance

When an evaluation target pattern includes a portion that extendsoutside the shape deformation tolerance of the pattern, the evaluationtarget pattern is determined as a defective pattern. However, asdescribed above, the contour data set extracted from an image includesnoise information, and thereby an incorrect determination may be madedue to a contour deformation caused by the noise. For this reason,incorrect detection of defective patterns due to noise included inimages is reduced by use of threshold determination in which a patternis determined as a defective pattern when a portion (defective portion1405) of the pattern outside the shape deformation tolerance of thepattern is larger than a predetermined value.

(3) Area

An evaluation target pattern in which the area ratio of the region 1407to the reference pattern is equal to or larger than N, or equal to orsmaller than M (where M<N) is determined as a defective pattern.

As has been described above, according to the present invention, areference pattern used to evaluate the shape of each of circuit patternsin electronic devices is generated from captured images of multiplecircuit patterns. This enables the generation of a reference patternwhich is suitable for circuit pattern production conditions and which isless influenced by a distortion of each of circuit patterns. Comparingan evaluation target pattern with this reference pattern allows theshape evaluation of the evaluation target pattern to be performed withhigh accuracy.

Second Embodiment

The foregoing embodiment 1 provides the description of the example inwhich the overlay position of contour data sets is determined based on aresult of matching between the design data and the contour data sets (orimages from which contours are extracted).

Instead, the overlaying accuracy can also be improved by detecting aslight shift due to a shape difference between the design data and theevaluation target pattern, a slight shift with rotation of a wafer orthe like after the matching of the contour data sets with the designdata, and then by making minor adjustment of the overlay position basedon the detection result.

FIG. 19 shows a processing flow for generating a contour composite imagewith minor adjustment of the overlay position by use of contour datasets.

Firstly, as described in Embodiment 1, each of the contour data sets isread (1901), the matching of the design data and the evaluation targetpattern is performed (1902), and thereby the shift amount is calculated(1903). FIG. 20A shows an example of two contour data sets overlaidbased on the shift amounts thus calculated. Although this is an extremeexample, a contour data set 2002 is inclined from a contour data set2001. In order to detect a rotation or a slight shift of a contour dataset from another one, matching between the contour data sets isperformed (1904), and thereby a position correction amount is calculated(1905).

Specifically, one of the contour data sets of the evaluation targetpattern, for example, the contour data set 2001, is used as a template,and the matching of the other evaluation target pattern, i.e. thecontour data set 2002 with the contour data set 2001 is performed. Withthis matching, a position correction amount (a rotation angle and apositional shift amount) 2003 is calculated as shown in FIG. 20B.

A method applicable to the pattern matching is one capable of finding amatching point accurately even when the template and the evaluationtarget pattern are different in size (in terms of the pattern shapedeformation due to process variations, it is often the case that apattern is simply expanded or contracted while keeping its originalpattern shape, except for certain shape anomaly) or even when theevaluation target pattern is rotated from the template. One example ofsuch method is the generalized Hough transform described on p. 215 of“dejitaru gazo shori (digital image processing) published by ComputerGraphic Arts Society (CG-ARTS).” However, it should not be understoodthat the method is limited to this, because various matching methodswell functioning even under the presence of a rotation angle betweenpatterns and pattern deformation have been proposed besides thegeneralized Hough transform. Then, finally, according to the positioncorrection amount 2003 of the evaluation target pattern detected throughthe matching between the contour data sets, the rotational adjustment ismade on the evaluation target pattern, and the contour data sets areoverlaid on each other at a point corresponding to the overlay position.

As described above, in the present invention, before the contour datasets are actually overlaid on each other, the matching between contourdata sets is performed using one of the contour data sets as a templatewhile allowing for a shape difference and rotation of one contour dataset from another set. Through this matching, the position correctionamount 2003 of the contour data set is calculated, and the position ofthe contour data set is corrected based on the position correctionamount 2003. Thereby, the contour data sets are overlaid on each otherwith high accuracy (1906), and a more accurate reference pattern for thepattern shape evaluation is generated (1907). Use of this referencepattern for comparison of an evaluation target pattern leads to moreaccurate shape evaluation of patterns.

Third Embodiment

Hereinafter, description will be provided for another embodiment formeasuring a process window.

The shape evaluation methods in Embodiments 1 and 2 have been describedas the case where the multiple patterns for the reference patterngeneration are prepared separately from the evaluation target pattern.Instead of this, the reference pattern may be generated from multipleevaluation target patterns, and the shapes of the evaluation targetpatterns are each evaluated by use of the reference pattern thusgenerated. In this way, the shape of each evaluation target pattern canbe evaluated relative to shape variation of the evaluation targetpatterns, that is, the shape of each evaluation target pattern can beevaluative in terms of a difference from an average shape of theevaluation target patterns.

For example, multiple patterns having the same shape on the design dataand being formed on different chips are imaged; the contour data setsare extracted from a captured image of each chip; and the contourdistribution data is generated. This contour distribution showsvariation in pattern shape among the chips, the variation caused byprocess variations. Thereafter, an average position of the contourdistribution is used to form the reference pattern. This referencepattern shows an average point of the pattern shapes which varies amongthe chips due to the process variations. By measuring the gap betweenthis reference pattern and each of the evaluation target patterns asdescribed in Embodiment 1, an evaluation can be made as to how much theevaluation target pattern deviates from the average point in the patternshape variation caused by the process variations.

Moreover, whether a pattern is defective or not is determined bycomparing this deviation range and the tolerance for pattern shapedeformation as shown in Embodiment 1. This quality determination isperformed for all the evaluation target patterns.

According to the present invention, by using the reference patterngenerated from multiple evaluation target patterns for the shapeevaluation of each of the evaluation target patterns, the evaluationtarget patterns can be evaluated relative to shape variation among theevaluation target patterns.

Fourth Embodiment

When a reference pattern is generated by use of multiple pattern imageswith relatively small pattern shape deformation due to processvariations, the reference pattern thus generated is free from small edgedeformation that may be otherwise caused by edge roughness and noise. Inrecent process techniques, contour data on patterns formed on a waferhas been increasingly used for calibration in an optical proximitycorrection (OPC) model. In the formation of the OPC model, an importanceis particularly placed on elimination of pattern deformation due tonoise included in images. For this reason, for the calibration, it iseffective to use a reference pattern generated from multiple patternsaffected by process variations only to a small extent.

For this purpose, the method of forming a contour composite and themethod of evaluating the shape by using the generated reference patternaccording to the foregoing embodiments are usable. The purpose of thisembodiment, however, is to detect and generate the reference patternfrom patterns with only small pattern shape deformation due to processvariations. It should be noted, here, that the shape of a referencepattern may be also largely deformed if the reference pattern isgenerated from patterns with large shape deformation. In a procedure offorming a composite of contour data sets as shown in FIG. 27, adetermination is made as to whether each of patterns is a non-defectivepattern or a defective pattern (2701), and then only the non-defectivepatterns are processed to form a contour composite. This processingenables the generation of a reference pattern free from both small edgedeformation due to edge roughness and noise, and large deformation dueto the process variations and the like. Specifically, the gap between apattern and design data, for example, the gap between each ofrepresentative points in a pattern and that of the design data ismeasured, and then the measured value is compared with a gap value(default value) tolerable for a non-defective pattern.

As has been described, in the present invention, the processing of:detecting a contour data set of a largely-deformed pattern through thepattern shape evaluation; and generating the contour composite from thecontour data sets excluding the detected contour data set areadditionally performed prior to the generation of a contour compositedescribed in Embodiments 1 to 3. Thus, the present invention enables thegeneration of a reference pattern suitable for OPC model calibration andpattern shape evaluation.

It should be noted that the technique of the present invention is widelyapplicable to apparatuses with which the shapes of circuit patterns ofelectronic devices manufactured by use of a wafer, reticle and the likeare evaluated based on the captured images of the circuit patterns.

1-15. (canceled)
 16. A pattern generating apparatus that generates areference pattern used to evaluate a shape of a circuit pattern of anelectronic device, the pattern generating apparatus comprising:reference pattern generating means for generating, from contour datasets of at least two circuit patterns, a reference pattern used in apattern test, wherein the reference pattern generating means determinespoints that cross the at least two contour data sets and, in a directionapplied to each portion of the patterns, respectively correspond tocontour data of one circuit pattern and to contour data of anothercircuit pattern, and generates the reference pattern based on extractionof an average position between the corresponding point of the contourdata of the one circuit pattern and the corresponding point of thecontour data of the other circuit pattern, or a center position betweenthe corresponding point of the contour data of the one circuit patternand the corresponding point of the contour data of the other circuitpattern.
 17. A pattern generating apparatus that generates a referencepattern used to evaluate a shape of a circuit pattern of an electronicdevice, the pattern generating apparatus comprising: reference patterngenerating means for generating, from contour data sets of at least twocircuit patterns, a reference pattern used in a pattern test, whereinthe reference pattern generating means executes contour fillingprocessing for a region interposed between the at least two contour datasets, and generates the reference pattern based on thinning processingperformed on the filled region.
 18. The pattern generating apparatusaccording to claim 16 or 17, further comprising: means for identifying aposition for overlaying the contour data sets on one another byperforming pattern matching between one contour data and another contourdata; and contour distribution data generating means for generatingcontour distribution data based on the identified position foroverlaying the contour data sets on one another.
 19. The patterngenerating apparatus according to claim 16 or 17, further comprising:means for identifying a position for overlaying the contour data sets onone another by performing pattern matching between design data and eachof the contour data sets; and contour distribution data generating meansfor generating contour distribution data based on the position foroverlaying the design data and each of the contour data sets.
 20. Thepattern generating apparatus according to claim 16 or 17, furthercomprising: contour distribution data generating means for comparing adefault value of the shape of the circuit pattern with a shape of eachof the contour data sets, and generating the contour distribution dataonly by using contour data that satisfies the default value of the shapeof the circuit pattern.
 21. The pattern generating apparatus accordingto claim 16 or 17, wherein the reference pattern generating meansidentifies a distribution of contours from the at least two contour datasets, and sets the reference pattern within a range of the distributionof contours.
 22. The pattern generating apparatus according to claim 16or 17, wherein the reference pattern generating means generates thereference pattern from the at least two contour data sets in referenceto the shape of the design data of the circuit pattern.
 23. A patternshape evaluating apparatus, comprising: the means for generating contourdata to be overlaid according to claim 16 or 17; reference patterngenerating means; and shape evaluation means for generating a shapeevaluation value of an evaluation target pattern with respect to thereference pattern by comparing the reference pattern with the evaluationtarget pattern.
 24. The pattern shape evaluating apparatus according toclaim 23, wherein the shape evaluation means includes qualitydetermination means for determining whether the evaluation targetpattern is defective or not, by using the shape evaluation value. 25.The pattern shape evaluating apparatus according to claim 23, wherein:as the shape evaluation value of the evaluation target pattern, a gapbetween the reference pattern and the evaluation target pattern ismeasured, one of an average of gaps, a dispersion of the gaps, or anarea ratio of the evaluation target pattern to the reference pattern iscalculated, or whether the evaluation target pattern exists outside orinside a pattern shape deformation tolerance provided to the referencepattern is determined, and the pattern shape evaluating apparatusfurther comprises quality determination means for determining whetherthe evaluation target pattern is defective or not, by comparing theshape evaluation value with a default value for determining whether theevaluation target pattern is defective or not.
 26. A pattern shapeevaluating apparatus, comprising: the means for generating contour datato be overlaid, the reference pattern generating means according toclaim 1 or 2; shape evaluation means for generating a shape evaluationvalue of an evaluation target pattern with respect to the referencepattern by comparing the reference pattern with the evaluation targetpattern, a quality determination means for determining whether theevaluation target pattern is defective or not; imaging means forobtaining a captured image of an evaluation target pattern and capturedimages of at least two circuit patterns for generating a referencepattern; means for extracting contour data sets of the circuit patternsfrom the captured images; and data storage means for storing thecaptured images, the contour data sets, the at least two contour datasets, the reference pattern, the shape evaluation value, and data on thequality determination result which are obtained by the pattern shapeevaluation.
 27. The pattern shape evaluating apparatus according toclaim 26, further comprising: means for generating, from design data ofthe circuit patterns, a recipe for obtaining a captured image of each ofthe circuit patterns by the imaging means.
 28. The pattern shapeevaluating apparatus according to claim 26, further comprising: a datadisplay means for displaying the at least two contour data sets, thereference pattern, and the data on the shape evaluation result.
 29. Thepattern shape evaluating apparatus according to claim 26, furthercomprising: data input means for reflecting instructions from a userinto the reference pattern generating means, the shape evaluation means,and the quality determination means, wherein the reference patterngenerating means, the shape evaluation means, and the qualitydetermination means generate the reference pattern and perform the shapeevaluation on the basis of instruction data from the data input means.30. The pattern generating apparatus according to claim 16 or 17,further comprising: data input means for reflecting instructions from auser into the reference pattern generating means, wherein the referencepattern generating means generates the reference pattern on the basis ofinstruction data from the data input means.
 31. The pattern shapeevaluating apparatus according to claim 28, wherein an image of a wafermap is generated, the wafer map indicating the shape evaluation valueand the quality determination result, and the image of the wafer map isdisplayed on the data display means.